Journal Article Lexical representation and development in a second language Get access N Jiang Department of English, Auburn University, Auburn, AL 36849, USA E-mail: auburn_jiangnan@hotmail.com Search for other works by this author on: Oxford Academic Google Scholar Applied Linguistics, Volume 21, Issue 1, March 2000, Pages 47–77, https://doi.org/10.1093/applin/21.1.47 Published: 01 2000

Introduction: Drug resistance to echinocandins, first-line drugs used treat Candida auris infection, is rapidly emerging. However, the accumulation of mutations in genes other than FKS1 (before an isolate develops via mutations), remains poorly understood. Methods: Four clinical cases and 29 isolates associated with incremental process echinocandin were collected analyzed using antifungal drug susceptibility testing genome sequencing assess evolution resistance. Findings: Six minimum...

Recently, DeepFake videos have developed rapidly, causing new security issues in society. Due to the rough spatiotemporal view, existing video-based detection methods struggle capture fine-grained information, resulting limited generalization ability. In addition, although transformer has achieved great success past few years, application of on deepfake video still needs be studied. To solve this problem, paper, we propose a novel Multiple Spatiotemporal Views Transformer (MSVT) with Local...

Abstract Background In the practical application of sarcopenia screening, there is a need for faster, time-saving, and community-friendly detection methods. The primary purpose this study was to perform screening in community-dwelling older adults investigate whether surface electromyogram (sEMG) from hand grip could potentially be used detect using machine learning (ML) methods with reasonable features extracted sEMG signals. secondary aim provide interpretability obtained ML models novel...

Self-supervised representation learning for visual pre-training has achieved remarkable success with sample (instance or pixel) discrimination and semantics discovery of instance, whereas there still exists a non-negligible gap between pre-trained model downstream dense prediction tasks. Concretely, these tasks require more accurate representation, in other words, the pixels from same object must belong to shared semantic category, which is lacking previous methods. In this work, we present...

Existing deepfake analysis methods are primarily based on discriminative models, which significantly limit their application scenarios. This paper aims to explore interactive by performing instruction tuning multi-modal large language models (MLLMs). will face challenges such as the lack of datasets and benchmarks, low training efficiency. To address these issues, we introduce (1) a GPT-assisted data construction process resulting in an instruction-following dataset called DFA-Instruct, (2)...

The tremendous number of sensors and smart objects deployed in the Internet Things (IoT) pose a huge potential for IoT real-time monitoring applications to detect react real world. insufficient capacity data processing has hampered growth applications. We focus on two issues processing: 1) how efficiently transform large raw sensing into meaningful complex event, 2) adapt complexity changeability business logic. This paper proposes universal event (CEP) mechanism monitoring. propose...

Different sampling strategies produce varying sample data, serve as the primary input data and directly affect accuracy of predictions in data-driven grid-based susceptibility models. This study analyzes variation debris flow maps (DFSMs) generated by various strategies. The area is Yingxiu region China, where six were applied, including three locations (deposition area, runout source area) two types (centroid polygon) for inventory. effectiveness 10 conditioning factors used to build model...

The global rate of Amphotericin B (AmB) resistance in

Abstract Gastrointestinal adenocarcinoma is a major cancer type for the digestive system, ranking as top cause of cancer-related deaths worldwide. While there has been extensive research on mutations in protein-coding regions, knowledge landscape its non-coding regulatory elements still insufficient. Combining analysis active enhancer profiles and genomic structural variation, we discovered validated lineage-specific super-enhancer MYB gastrointestinal adenocarcinoma. This composed...

Automatic Speech Recognition (ASR) in conversational settings presents unique challenges, including extracting relevant contextual information from previous turns. Due to irrelevant content, error propagation, and redundancy, existing methods struggle extract longer more effective contexts. To address this issue, we introduce a novel ASR system, extending the Conformer encoder-decoder model with cross-modal representation. Our approach leverages extractor that combines pre-trained speech...

Cyber Security breaches and attacks are on the ascendancy as corporations, governments, universities, private individuals conducting their business personal transactions web. This increasing participating web necessitates that robust efficient cyber security systems need to be put in place by these entities safeguard assets. Intelligent Systems needs employed buttress protocols established cloud computing for proper decision-making, which may depend effective knowledge representation....

Mobile ad-hoc networks (MANETs) have attracted great research interest in recent years. Among many issues, lack of motivation for participating nodes to collaborate forms a major obstacle the adoption MANETs. Many contemporary collaboration enforcement techniques employ reputation mechanisms avoid and penalize malicious participants. Reputation in- formation is propagated among participants updated based on complicated trust relationships thwart false accusation benign nodes. The...

In recent years, services based on cloud computing have been used more and widely. Stakeholders paid attention the quality of service. But most them don't know how to evaluate This paper proposes a comprehensive, structurized, hierarchical model service, which concerned not only IT features but also service The was constructed by 6 characteristics, i.e., usability, security, reliability, tangibility, responsiveness, empathy. We divided each characteristic into several subcharacteristics....

As an essential form of knowledge representation, taxonomies are widely used in various downstream natural language processing tasks. However, with the continuously rising new concepts, many existing unable to maintain coverage by manual expansion. In this paper, we propose TEMP, a self-supervised taxonomy expansion method, which predicts position concepts ranking generated taxonomy-paths. For first time, TEMP employs pre-trained contextual encoders construction and hypernym detection...

Introduction Candida palmioleophila is a rare human pathogenic fungus, which has been poorly characterized at the genome level. In this study, we reported first fatal case of C. infection in China and investigate microevolution host environment. Methods A series stains were collected from patient different time points for routine microbial drug sensitivity testing. The isolate 07202534 was identified by de novo whole sequencing. vitro vivo genetic evolutionary characteristics discussed based...

This paper is the system description of DKU-MSXF System for track1, track2 and track3 VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). For Track 1, we utilize a network structure based on ResNet training. By constructing cross-age QMF training set, achieve substantial improvement in performance. 2, inherite pre-trained model from 1 conducte mixed by incorporating VoxBlink-clean dataset. In comparison to models data exhibit performance more than 10% relatively. Track3, semi-supervised...

Utilizing the pseudo-labeling algorithm with large-scale unlabeled data becomes crucial for semi-supervised domain adaptation in speaker verification tasks. In this paper, we propose a novel method named Multi-objective Progressive Clustering (MoPC), specifically designed adaptation. Firstly, utilize limited labeled from target to derive domain-specific descriptors based on multiple distinct objectives, namely within-graph denoising, intra-class denoising and inter-class denoising. Then,...

Estimating individual treatment effects in networked observational data is a crucial and increasingly recognized problem. One major challenge of this problem violating the stable unit value assumption (SUTVA), which posits that unit’s outcome independent others’ assignments. However, network data, influenced not only by its (i.e., direct effect) but also treatments others spillover since presence interference. Moreover, interference from other units always heterogeneous (e.g., friends with...